{"title":"符号计算中的基准测试Rôle(立场文件)","authors":"J. Davenport","doi":"10.1109/SYNASC.2018.00050","DOIUrl":null,"url":null,"abstract":"There is little doubt that, in the minds of most symbolic computation researchers, the ideal paper consists of a problem statement, a new algorithm, a complexity analysis and preferably a few validating examples. There are many such great papers. This paradigm has served computer algebra well for many years, and indeed continues to do so where it is applicable. However, it is much less applicable to sparse problems, where there are many NP-hardness results, or to many problems coming from algebraic geometry, where the worst-case complexity seems to be rare. We argue that, in these cases, the field should take a leaf out of the practices of the SAT-solving community, and adopt systematic benchmarking, and benchmarking contests, as a way measuring (and stimulating) progress. This would involve a change of culture.","PeriodicalId":273805,"journal":{"name":"2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Rôle of Benchmarking in Symbolic Computation (Position Paper)\",\"authors\":\"J. Davenport\",\"doi\":\"10.1109/SYNASC.2018.00050\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There is little doubt that, in the minds of most symbolic computation researchers, the ideal paper consists of a problem statement, a new algorithm, a complexity analysis and preferably a few validating examples. There are many such great papers. This paradigm has served computer algebra well for many years, and indeed continues to do so where it is applicable. However, it is much less applicable to sparse problems, where there are many NP-hardness results, or to many problems coming from algebraic geometry, where the worst-case complexity seems to be rare. We argue that, in these cases, the field should take a leaf out of the practices of the SAT-solving community, and adopt systematic benchmarking, and benchmarking contests, as a way measuring (and stimulating) progress. This would involve a change of culture.\",\"PeriodicalId\":273805,\"journal\":{\"name\":\"2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SYNASC.2018.00050\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SYNASC.2018.00050","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Rôle of Benchmarking in Symbolic Computation (Position Paper)
There is little doubt that, in the minds of most symbolic computation researchers, the ideal paper consists of a problem statement, a new algorithm, a complexity analysis and preferably a few validating examples. There are many such great papers. This paradigm has served computer algebra well for many years, and indeed continues to do so where it is applicable. However, it is much less applicable to sparse problems, where there are many NP-hardness results, or to many problems coming from algebraic geometry, where the worst-case complexity seems to be rare. We argue that, in these cases, the field should take a leaf out of the practices of the SAT-solving community, and adopt systematic benchmarking, and benchmarking contests, as a way measuring (and stimulating) progress. This would involve a change of culture.